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生物医学工程与生物力学

Biomedical Engineering and Biomechanics

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张黄河

职称：副研究员

单位：山东大学

社会任职：Elsevier期刊Healthcare and Rehabilitation, 青年编委/特邀客座编辑（Lead Guest Editor）；Elsevier期刊Wearable Technology，特邀客座编辑（Lead Guest Editor）

个人简介

张黄河，副研究员，海外博士后引才专项入选者，山东省优海外优青，泰山学者青年专家，全国创新创业优秀博士后，美国斯蒂文斯卓越博士。 研究领域：康复机器人、可穿戴技术、便携式步态分析与康复，人机交互。

教育经历

学术贡献

  • 1、[1] H. Zhang, C. Wu, Y. Huang, R. Song, D. Zanotto and S. Agrawal. Fall Risk Prediction Using Instrumented Footwear in Institutionalized Older Adults. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2024 Dec 02.
  • 2、[2] H. Zhang, Wu C, Huang Y, Li X, Ma X, Song R, Agrawal SK. 2D Deep Convolutional Neural Networks for Estimating Stride Length and Velocity in Institutionalized Older Adults. IEEE Sensors Journal. 2024 Jun 18.
  • 3、[3] H. Zhang, S. Li, Q. Zhao, A. Rao, Y. Guo and D. Zanotto. “Reinforcement Learning-Based Adaptive Biofeedback Engine for Overground Walking Speed Training”, IEEE Robotics and Automation Letters, 2022, June 30
  • 4、[4] H. Zhang, T. Duong, A. Rao, P. Mazzoni, S. Agrawal, Y. Guo and D. Zanotto. “Transductive Learning Models for Accurate Ambulatory Gait Analysis in Elderly Residents of Assisted Living Facilities”, IEEE Transactions on Neural Systems and Rehabilitation Engineering 30 (2022): 124-134.
  • 5、[5] H. Zhang, Y. Guo and D. Zanotto. “Accurate Ambulatory Gait Analysis in Walking and Running Using Machine Learning Models”, IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE).2020, 28, 191-202.
  • 6、[6] H. Zhang, D. Zanotto and S.K. Agrawal. “Estimating CoP Trajectories and Kinematic Gait Parameters in Walking and Running Using Instrumented Insoles”, IEEE Robotics and Automation Letters. 2017, 2, 2159-2165.
  • 7、[7] H. Zhang, Z. Chen, D. Zanotto and Y. Guo. “Robot-Assisted and Wearable Sensor-Mediated Autonomous Gait Analysis”, IEEE International Conference on Robotics and Automation (ICRA), Paris, 2020.
  • 8、[8] H. Zhang, M. Tay, Z. Suar, M. Kurt and D. Zanotto. “Regression Models for Estimating Kinematic Gait Parameters with Instrumented Footwear”, 7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, Enschede, 2018.
  • 9、[9] J. Wang, Z. Guan, J. Cai, X. Li, C. Wu, X. Ma, Y. Li, R. Song and H. Zhang. “Deep Neural Networks for Gait Cycle Percentage Prediction in Frail Older Adults Using a Foot-mounted IMU,” IEEE-ROBIO 2024. Accept.
  • 10、[10] Z. Feng, Z. Jiang, H. Liu, W. Wang, Y. Wang, C. Lu, X. Ma, Y. Li, R. Song and H. Zhang. “Machine Learning Models for Gait Phases Detection Using Surface Electromyography Signals”17th International Conference on Intelligent Robotics and Applications (ICIRA2024), Springer. Accept.
  • 11、[11] Y. Zhang, J. Cai, X. Li, C. Wu, X. Ma, R. Song and H. Zhang. “End-to-End Deep Learning Models for Estimating Stride Length in Frail Older Adults”, CFIMA 2024: The 2nd International Conference on Frontiers of Intelligent Manufacturing and Automation, August 9-11, Baotou, China, 2024.
  • 12、[12] Y. Sun, J. Wang, Z. Wang, J. Li, Y. Li, R. Song and H. Zhang. “Gait Phase Detection and Prediction with Machine Learning Models Based on sEMG”, The International Conference on Artificial Intelligence, Human-Computer Interaction and Robotics, Accept.

工作经历